Antenna Season Report Notebook¶

Josh Dillon, Last Revised January 2022

This notebook examines an individual antenna's performance over a whole season. This notebook parses information from each nightly rtp_summarynotebook (as saved to .csvs) and builds a table describing antenna performance. It also reproduces per-antenna plots from each auto_metrics notebook pertinent to the specific antenna.

In [1]:
import os
from IPython.display import display, HTML
display(HTML("<style>.container { width:100% !important; }</style>"))
In [2]:
# If you want to run this notebook locally, copy the output of the next cell into the next line of this cell.
# antenna = "004"
# csv_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/_rtp_summary_'
# auto_metrics_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/auto_metrics_inspect'
# os.environ["ANTENNA"] = antenna
# os.environ["CSV_FOLDER"] = csv_folder
# os.environ["AUTO_METRICS_FOLDER"] = auto_metrics_folder
In [3]:
# Use environment variables to figure out path to the csvs and auto_metrics
antenna = str(int(os.environ["ANTENNA"]))
csv_folder = os.environ["CSV_FOLDER"]
auto_metrics_folder = os.environ["AUTO_METRICS_FOLDER"]
print(f'antenna = "{antenna}"')
print(f'csv_folder = "{csv_folder}"')
print(f'auto_metrics_folder = "{auto_metrics_folder}"')

antenna = "333"
csv_folder = "/home/obs/src/H6C_Notebooks/_rtp_summary_"
auto_metrics_folder = "/home/obs/src/H6C_Notebooks/auto_metrics_inspect"
In [4]:
display(HTML(f'<h1 style=font-size:50px><u>Antenna {antenna} Report</u><p></p></h1>'))

Antenna 333 Report

In [5]:
import numpy as np
import pandas as pd
pd.set_option('display.max_rows', 1000)
import glob
import re
from hera_notebook_templates.utils import status_colors, Antenna
In [6]:
# load csvs and auto_metrics htmls in reverse chronological order
csvs = sorted(glob.glob(os.path.join(csv_folder, 'rtp_summary_table*.csv')))[::-1]
print(f'Found {len(csvs)} csvs in {csv_folder}')
auto_metric_htmls = sorted(glob.glob(auto_metrics_folder + '/auto_metrics_inspect_*.html'))[::-1]
print(f'Found {len(auto_metric_htmls)} auto_metrics notebooks in {auto_metrics_folder}')

Found 31 csvs in /home/obs/src/H6C_Notebooks/_rtp_summary_
Found 31 auto_metrics notebooks in /home/obs/src/H6C_Notebooks/auto_metrics_inspect
In [7]:
# Per-season options
mean_round_modz_cut = 4
dead_cut = 0.4
crossed_cut = 0.0

def jd_to_summary_url(jd):
    return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H6C_Notebooks/blob/main/_rtp_summary_/rtp_summary_{jd}.html'

def jd_to_auto_metrics_url(jd):
    return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H6C_Notebooks/blob/main/auto_metrics_inspect/auto_metrics_inspect_{jd}.html'

Load relevant info from summary CSVs¶

In [8]:
this_antenna = None
jds = []

# parse information about antennas and nodes
for csv in csvs:
    df = pd.read_csv(csv)
    for n in range(len(df)):
        # Add this day to the antenna
        row = df.loc[n]
        if isinstance(row['Ant'], str) and '<a href' in row['Ant']:
            antnum = int(row['Ant'].split('</a>')[0].split('>')[-1]) # it's a link, extract antnum
        else:
            antnum = int(row['Ant'])
        if antnum != int(antenna):
            continue
        
        if np.issubdtype(type(row['Node']), np.integer):
            row['Node'] = str(row['Node'])
        if type(row['Node']) == str and row['Node'].isnumeric():
            row['Node'] = 'N' + ('0' if len(row['Node']) == 1 else '') + row['Node']
            
        if this_antenna is None:
            this_antenna = Antenna(row['Ant'], row['Node'])
        jd = [int(s) for s in re.split('_|\.', csv) if s.isdigit()][-1]
        jds.append(jd)
        this_antenna.add_day(jd, row)
        break
In [9]:
# build dataframe
to_show = {'JDs': [f'<a href="{jd_to_summary_url(jd)}" target="_blank">{jd}</a>' for jd in jds]}
to_show['A Priori Status'] = [this_antenna.statuses[jd] for jd in jds]

df = pd.DataFrame(to_show)

# create bar chart columns for flagging percentages:
bar_cols = {}
bar_cols['Auto Metrics Flags'] = [this_antenna.auto_flags[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jee)'] = [this_antenna.dead_flags_Jee[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jnn)'] = [this_antenna.dead_flags_Jnn[jd] for jd in jds]
bar_cols['Crossed Fraction in Ant Metrics'] = [this_antenna.crossed_flags[jd] for jd in jds]
bar_cols['Flag Fraction Before Redcal'] = [this_antenna.flags_before_redcal[jd] for jd in jds]
bar_cols['Flagged By Redcal chi^2 Fraction'] = [this_antenna.redcal_flags[jd] for jd in jds]
for col in bar_cols:
    df[col] = bar_cols[col]

z_score_cols = {}
z_score_cols['ee Shape Modified Z-Score'] = [this_antenna.ee_shape_zs[jd] for jd in jds]
z_score_cols['nn Shape Modified Z-Score'] = [this_antenna.nn_shape_zs[jd] for jd in jds]
z_score_cols['ee Power Modified Z-Score'] = [this_antenna.ee_power_zs[jd] for jd in jds]
z_score_cols['nn Power Modified Z-Score'] = [this_antenna.nn_power_zs[jd] for jd in jds]
z_score_cols['ee Temporal Variability Modified Z-Score'] = [this_antenna.ee_temp_var_zs[jd] for jd in jds]
z_score_cols['nn Temporal Variability Modified Z-Score'] = [this_antenna.nn_temp_var_zs[jd] for jd in jds]
z_score_cols['ee Temporal Discontinuties Modified Z-Score'] = [this_antenna.ee_temp_discon_zs[jd] for jd in jds]
z_score_cols['nn Temporal Discontinuties Modified Z-Score'] = [this_antenna.nn_temp_discon_zs[jd] for jd in jds]
for col in z_score_cols:
    df[col] = z_score_cols[col]

ant_metrics_cols = {}
ant_metrics_cols['Average Dead Ant Metric (Jee)'] = [this_antenna.Jee_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Dead Ant Metric (Jnn)'] = [this_antenna.Jnn_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Crossed Ant Metric'] = [this_antenna.crossed_metrics[jd] for jd in jds]
for col in ant_metrics_cols:
    df[col] = ant_metrics_cols[col]

redcal_cols = {}
redcal_cols['Median chi^2 Per Antenna (Jee)'] = [this_antenna.Jee_chisqs[jd] for jd in jds]
redcal_cols['Median chi^2 Per Antenna (Jnn)'] = [this_antenna.Jnn_chisqs[jd] for jd in jds]   
for col in redcal_cols:
    df[col] = redcal_cols[col]

# style dataframe
table = df.style.hide_index()\
          .applymap(lambda val: f'background-color: {status_colors[val]}' if val in status_colors else '', subset=['A Priori Status']) \
          .background_gradient(cmap='viridis', vmax=mean_round_modz_cut * 3, vmin=0, axis=None, subset=list(z_score_cols.keys())) \
          .background_gradient(cmap='bwr_r', vmin=dead_cut-.25, vmax=dead_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
          .background_gradient(cmap='bwr_r', vmin=crossed_cut-.25, vmax=crossed_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
          .background_gradient(cmap='plasma', vmax=4, vmin=1, axis=None, subset=list(redcal_cols.keys())) \
          .applymap(lambda val: 'font-weight: bold' if val < dead_cut else '', subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
          .applymap(lambda val: 'font-weight: bold' if val < crossed_cut else '', subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
          .applymap(lambda val: 'font-weight: bold' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
          .applymap(lambda val: 'color: red' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
          .bar(subset=list(bar_cols.keys()), vmin=0, vmax=1) \
          .format({col: '{:,.4f}'.format for col in z_score_cols}) \
          .format({col: '{:,.4f}'.format for col in ant_metrics_cols}) \
          .format('{:,.2%}', na_rep='-', subset=list(bar_cols.keys())) \
          .set_table_styles([dict(selector="th",props=[('max-width', f'70pt')])])

Table 1: Per-Night RTP Summary Info For This Atenna¶

This table reproduces each night's row for this antenna from the RTP Summary notebooks. For more info on the columns, see those notebooks, linked in the JD column.

In [10]:
display(HTML(f'<h2>Antenna {antenna}, Node {this_antenna.node}:</h2>'))
HTML(table.render(render_links=True, escape=False))

Antenna 333, Node N12:

Out[10]:
JDs A Priori Status Auto Metrics Flags Dead Fraction in Ant Metrics (Jee) Dead Fraction in Ant Metrics (Jnn) Crossed Fraction in Ant Metrics Flag Fraction Before Redcal Flagged By Redcal chi^2 Fraction ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score Average Dead Ant Metric (Jee) Average Dead Ant Metric (Jnn) Average Crossed Ant Metric Median chi^2 Per Antenna (Jee) Median chi^2 Per Antenna (Jnn)
2460014 dish_maintenance 0.00% 0.00% 0.00% 0.00% - - 3.336566 1.772013 -0.641184 -1.152165 -0.985843 -0.116594 1.196382 1.886465 0.4015 0.4371 0.3276 nan nan
2460013 dish_maintenance 0.00% 0.00% 0.00% 0.00% - - 3.104829 1.380475 -0.460796 -1.250012 -0.877196 -0.709793 1.409136 0.311252 0.4212 0.4481 0.3288 nan nan
2460012 dish_maintenance 0.00% 0.00% 0.00% 0.00% - - 2.899224 1.257994 -0.712538 -1.407028 -0.784309 -0.648938 1.679014 0.612793 0.4225 0.4459 0.3252 nan nan
2460011 dish_maintenance 0.00% 0.00% 0.00% 0.00% - - 3.383476 1.297865 -1.266680 -1.934321 -1.555381 -1.603304 1.337117 1.096582 0.4324 0.4548 0.3341 nan nan
2460010 dish_maintenance 100.00% 0.00% 0.00% 0.00% - - 4.257827 3.139857 -0.982429 -1.331950 -0.929052 -1.136950 1.506394 1.160638 0.4385 0.4576 0.3343 nan nan
2460009 dish_maintenance 0.00% 0.00% 0.00% 0.00% - - 3.140877 2.097344 -0.905552 -1.393408 -0.896438 -0.738336 0.333615 0.980311 0.4476 0.4684 0.3404 nan nan
2460008 dish_maintenance 100.00% 0.00% 0.00% 0.00% - - 4.389317 3.437412 -1.116640 -1.647481 -0.551489 -0.605659 2.938008 2.262184 0.4672 0.4981 0.3254 nan nan
2460007 dish_maintenance 0.00% 0.00% 0.00% 0.00% - - 3.193395 3.617395 -0.662156 -1.118054 -1.041242 -0.535382 1.103649 0.544815 0.4435 0.4616 0.3225 nan nan
2459999 dish_maintenance 0.00% 98.91% 99.16% 0.00% - - nan nan nan nan nan nan nan nan 0.2357 0.2411 0.1798 nan nan
2459998 dish_maintenance 0.00% 0.00% 0.00% 0.00% - - 2.725431 3.418674 -0.544429 -1.065152 -0.340214 -0.301472 3.381177 0.139160 0.4511 0.4732 0.3493 nan nan
2459997 dish_maintenance 0.00% 0.00% 0.00% 0.00% - - 2.917948 3.726712 -0.700773 -1.050513 -0.506218 -0.381742 2.900019 0.476185 0.4683 0.4912 0.3545 nan nan
2459996 dish_maintenance 0.00% 0.00% 0.00% 0.00% - - 3.091491 3.294689 -0.564896 -1.248732 -1.122637 -0.860503 1.156613 1.218492 0.4771 0.4964 0.3697 nan nan
2459995 dish_maintenance 0.00% 0.00% 0.00% 0.00% - - 2.836774 3.542468 -1.019619 -1.466326 -1.020941 -0.922013 0.886727 1.324716 0.4681 0.4902 0.3565 nan nan
2459994 dish_maintenance 0.00% 0.00% 0.00% 0.00% - - 2.848720 3.918036 -0.929384 -1.239115 -0.607036 -0.693955 1.625446 1.461197 0.4589 0.4808 0.3484 nan nan
2459993 dish_maintenance 100.00% 100.00% 100.00% 0.00% - - nan nan inf inf nan nan nan nan nan nan nan nan nan
2459991 dish_maintenance 100.00% 0.00% 0.00% 0.00% - - 3.807416 4.911504 -0.997134 -1.248146 -0.443735 -0.602600 0.746422 1.200271 0.4641 0.4809 0.3558 nan nan
2459990 dish_maintenance 100.00% 0.00% 0.00% 0.00% - - 3.021491 4.170357 -0.952348 -1.232149 -0.199446 -0.741559 0.721505 0.248192 0.4612 0.4815 0.3524 nan nan
2459989 dish_maintenance 100.00% 0.00% 0.00% 0.00% - - 2.670614 4.295308 -0.872789 -0.994343 -0.358811 -0.875093 0.812861 -0.066104 0.4570 0.4820 0.3548 nan nan
2459988 dish_maintenance 100.00% 0.00% 0.00% 0.00% - - 3.399969 5.012673 -1.121158 -1.317481 -0.230640 -1.122889 0.487088 1.309578 0.4627 0.4858 0.3469 nan nan
2459987 dish_maintenance 0.00% 0.00% 0.00% 0.00% - - 2.335218 3.852628 -1.146164 -1.285207 -0.964029 -0.678735 0.404022 -0.343844 0.4746 0.4941 0.3477 nan nan
2459986 dish_maintenance 100.00% 0.00% 0.00% 0.00% - - 3.547121 4.849885 -1.169252 -1.380021 -0.592721 0.559258 2.271921 2.912274 0.4864 0.5147 0.3212 nan nan
2459985 dish_maintenance 0.00% 0.00% 0.00% 0.00% - - 2.859376 3.659403 -1.105556 -0.832202 -0.940720 -0.857818 1.400290 2.821170 0.4765 0.4990 0.3621 nan nan
2459984 dish_maintenance 0.00% 0.00% 0.00% 0.00% - - 1.462085 3.284846 -1.117251 -0.683183 0.711760 0.027351 0.983110 -0.566425 0.4915 0.5182 0.3533 nan nan
2459983 dish_maintenance 0.00% 0.00% 0.00% 0.00% - - 3.169349 3.078688 -1.021321 -1.312067 -0.322269 -0.591609 2.094355 1.882217 0.4879 0.5236 0.3284 nan nan
2459982 dish_maintenance 0.00% 0.00% 0.00% 0.00% - - 1.428319 3.340278 -0.697509 -1.017310 -0.910945 -0.685680 1.262283 1.266994 0.5233 0.5549 0.3148 nan nan
2459981 dish_maintenance 0.00% 0.00% 0.00% 0.00% - - 3.002578 1.407312 -1.235667 -1.421821 -0.054187 -0.879925 0.556057 0.655889 0.4680 0.5019 0.3635 nan nan
2459980 dish_maintenance 0.00% 0.00% 0.00% 0.00% - - 2.752780 1.638763 -0.675387 -1.511657 -0.081131 -0.361691 2.306017 1.235396 0.4865 0.5263 0.3280 nan nan
2459979 dish_maintenance 0.00% 0.00% 0.00% 0.00% - - 3.360327 2.249384 -0.696267 -1.447878 0.275818 -1.158739 0.417742 -0.217037 0.4524 0.4964 0.3633 nan nan
2459978 dish_maintenance 0.00% 0.00% 0.00% 0.00% - - 3.422795 2.211720 -0.706880 -1.488787 0.221169 -0.766941 0.206660 0.066232 0.4504 0.4934 0.3714 nan nan
2459977 dish_maintenance 0.00% 0.00% 0.00% 0.00% - - 3.267988 1.910924 -0.591764 -1.448899 -0.383596 -0.911745 0.258685 0.100305 0.4162 0.4519 0.3250 nan nan
2459976 dish_maintenance 0.00% 0.00% 0.00% 0.00% - - 3.323595 2.155914 -0.663860 -1.544192 -0.023240 -0.751211 0.875032 0.739640 0.4534 0.4973 0.3688 nan nan

Load antenna metric spectra and waterfalls from auto_metrics notebooks.¶

In [11]:
htmls_to_display = []
for am_html in auto_metric_htmls:
    html_to_display = ''
    # read html into a list of lines
    with open(am_html) as f:
        lines = f.readlines()
    
    # find section with this antenna's metric plots and add to html_to_display
    jd = [int(s) for s in re.split('_|\.', am_html) if s.isdigit()][-1]
    try:
        section_start_line = lines.index(f'<h2>Antenna {antenna}: {jd}</h2>\n')
    except ValueError:
        continue
    html_to_display += lines[section_start_line].replace(str(jd), f'<a href="{jd_to_auto_metrics_url(jd)}" target="_blank">{jd}</a>')
    for line in lines[section_start_line + 1:]:
        html_to_display += line
        if '<hr' in line:
            htmls_to_display.append(html_to_display)
            break

Figure 1: Antenna autocorrelation metric spectra and waterfalls.¶

These figures are reproduced from auto_metrics notebooks. For more info on the specific plots and metrics, see those notebooks (linked at the JD). The most recent 100 days (at most) are shown.

In [12]:
for i, html_to_display in enumerate(htmls_to_display):
    if i == 100:
        break
    display(HTML(html_to_display))

Antenna 333: 2460014

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
333 N12 dish_maintenance ee Shape 3.336566 3.336566 1.772013 -0.641184 -1.152165 -0.985843 -0.116594 1.196382 1.886465

Antenna 333: 2460013

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
333 N12 dish_maintenance ee Shape 3.104829 3.104829 1.380475 -0.460796 -1.250012 -0.877196 -0.709793 1.409136 0.311252

Antenna 333: 2460012

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
333 N12 dish_maintenance ee Shape 2.899224 2.899224 1.257994 -0.712538 -1.407028 -0.784309 -0.648938 1.679014 0.612793

Antenna 333: 2460011

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
333 N12 dish_maintenance ee Shape 3.383476 3.383476 1.297865 -1.266680 -1.934321 -1.555381 -1.603304 1.337117 1.096582

Antenna 333: 2460010

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
333 N12 dish_maintenance ee Shape 4.257827 4.257827 3.139857 -0.982429 -1.331950 -0.929052 -1.136950 1.506394 1.160638

Antenna 333: 2460009

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
333 N12 dish_maintenance ee Shape 3.140877 3.140877 2.097344 -0.905552 -1.393408 -0.896438 -0.738336 0.333615 0.980311

Antenna 333: 2460008

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
333 N12 dish_maintenance ee Shape 4.389317 3.437412 4.389317 -1.647481 -1.116640 -0.605659 -0.551489 2.262184 2.938008

Antenna 333: 2460007

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
333 N12 dish_maintenance nn Shape 3.617395 3.193395 3.617395 -0.662156 -1.118054 -1.041242 -0.535382 1.103649 0.544815

Antenna 333: 2459999

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
333 N12 dish_maintenance nn Shape nan nan nan nan nan nan nan nan nan

Antenna 333: 2459998

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
333 N12 dish_maintenance nn Shape 3.418674 2.725431 3.418674 -0.544429 -1.065152 -0.340214 -0.301472 3.381177 0.139160

Antenna 333: 2459997

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
333 N12 dish_maintenance nn Shape 3.726712 2.917948 3.726712 -0.700773 -1.050513 -0.506218 -0.381742 2.900019 0.476185

Antenna 333: 2459996

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
333 N12 dish_maintenance nn Shape 3.294689 3.091491 3.294689 -0.564896 -1.248732 -1.122637 -0.860503 1.156613 1.218492

Antenna 333: 2459995

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
333 N12 dish_maintenance nn Shape 3.542468 2.836774 3.542468 -1.019619 -1.466326 -1.020941 -0.922013 0.886727 1.324716

Antenna 333: 2459994

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
333 N12 dish_maintenance nn Shape 3.918036 2.848720 3.918036 -0.929384 -1.239115 -0.607036 -0.693955 1.625446 1.461197

Antenna 333: 2459993

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
333 N12 dish_maintenance ee Shape nan nan nan inf inf nan nan nan nan

Antenna 333: 2459991

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
333 N12 dish_maintenance nn Shape 4.911504 3.807416 4.911504 -0.997134 -1.248146 -0.443735 -0.602600 0.746422 1.200271

Antenna 333: 2459990

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
333 N12 dish_maintenance nn Shape 4.170357 4.170357 3.021491 -1.232149 -0.952348 -0.741559 -0.199446 0.248192 0.721505

Antenna 333: 2459989

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
333 N12 dish_maintenance nn Shape 4.295308 4.295308 2.670614 -0.994343 -0.872789 -0.875093 -0.358811 -0.066104 0.812861

Antenna 333: 2459988

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
333 N12 dish_maintenance nn Shape 5.012673 5.012673 3.399969 -1.317481 -1.121158 -1.122889 -0.230640 1.309578 0.487088

Antenna 333: 2459987

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
333 N12 dish_maintenance nn Shape 3.852628 2.335218 3.852628 -1.146164 -1.285207 -0.964029 -0.678735 0.404022 -0.343844

Antenna 333: 2459986

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
333 N12 dish_maintenance nn Shape 4.849885 4.849885 3.547121 -1.380021 -1.169252 0.559258 -0.592721 2.912274 2.271921

Antenna 333: 2459985

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
333 N12 dish_maintenance nn Shape 3.659403 3.659403 2.859376 -0.832202 -1.105556 -0.857818 -0.940720 2.821170 1.400290

Antenna 333: 2459984

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
333 N12 dish_maintenance nn Shape 3.284846 1.462085 3.284846 -1.117251 -0.683183 0.711760 0.027351 0.983110 -0.566425

Antenna 333: 2459983

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
333 N12 dish_maintenance ee Shape 3.169349 3.169349 3.078688 -1.021321 -1.312067 -0.322269 -0.591609 2.094355 1.882217

Antenna 333: 2459982

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
333 N12 dish_maintenance nn Shape 3.340278 1.428319 3.340278 -0.697509 -1.017310 -0.910945 -0.685680 1.262283 1.266994

Antenna 333: 2459981

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
333 N12 dish_maintenance ee Shape 3.002578 1.407312 3.002578 -1.421821 -1.235667 -0.879925 -0.054187 0.655889 0.556057

Antenna 333: 2459980

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
333 N12 dish_maintenance ee Shape 2.752780 1.638763 2.752780 -1.511657 -0.675387 -0.361691 -0.081131 1.235396 2.306017

Antenna 333: 2459979

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
333 N12 dish_maintenance ee Shape 3.360327 3.360327 2.249384 -0.696267 -1.447878 0.275818 -1.158739 0.417742 -0.217037

Antenna 333: 2459978

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
333 N12 dish_maintenance ee Shape 3.422795 2.211720 3.422795 -1.488787 -0.706880 -0.766941 0.221169 0.066232 0.206660

Antenna 333: 2459977

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
333 N12 dish_maintenance ee Shape 3.267988 3.267988 1.910924 -0.591764 -1.448899 -0.383596 -0.911745 0.258685 0.100305

Antenna 333: 2459976

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
333 N12 dish_maintenance ee Shape 3.323595 2.155914 3.323595 -1.544192 -0.663860 -0.751211 -0.023240 0.739640 0.875032
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